Social- and Interactive-Television
Applications Based on Real-Time Ambient-Audio Identification
Michael Fink
Center for Neural Computation, Hebrew University of Jerusalem,
Jerusalem 91904, Israel
fink@huji.ac.il
Michele Covell and Shumeet Baluja
Google Research, Google Inc.,
1600 Amphitheatre Parkway, Mountain View CA 94043
covell@google.com and shumeet@google.com
Abstract
This paper describes mass personalization, a
framework for combining mass media with a highly
personalized Web-based experience. We introduce
four
applications
for mass
personalization:
personalized content
layers, ad hoc
social
communities, real-time popularity ratings and
virtual media library services. Using the ambient
audio originating from the television, the four
applications are available with no more effort than
simple television channel surfing. Our audio
identification system does not use dedicated
interactive TV hardware and does not compromise
the user’s privacy. Feasibility tests of the proposed
applications are provided both with controlled
conversational interference and with “living-room”
evaluations.
1. Introduction
“Mass media is the term used to denote, as a class,
that section of the media specifically conceived and
designed to reach a very large audience… forming
a mass society with special characteristics, notably
atomization or lack of social connections”
(en. wikipedia.org).
These characteristics of mass media contrast
sharply with the World Wide Web. Mass-media
channels typically provide limited content to many
people;
the Web provides vast amounts of
information, most of interest to few. Mass-media
channels
typically
beget
passive,
largely
anonymous, consumption, while the Web provides
many
interactive opportunities
like chatting,
emailing and trading. Our goal is to combine the
best of both worlds: integrating the relaxing and
effortless experience of mass-media content with
the interactive and personalized potential of the
Web, providing mass